How Big Data Analytics May Help Governments Protect Us
The primary role of government is to protect the safety and well-being of its citizens.
Since 2000, statistics reveal that the amount of information being captured by the federal government is increasing exponentially and, since 2013, big data capture is expected to double as each year passes.
Analysis of such data is nothing new. As far back as 1967, the then-Office of Education and Office of Economic Development launched a program that spent more than $600 million in an attempt to correlate low household income with academic achievement. And that was just the beginning.
The information that can now be obtained from government databases is enormous; but with government budgets under continual strain, Sean Brophy of Tableau Software explains that the pressure is on for “agencies to find and use higher-value, more flexible tools, especially ones that help them see their data faster and clearer.”
Not surprisingly, that has encouraged a new generation of Big Data enterprises; from BI suites from the likes of Japersoft and Pentaho to dedicated flexible big data analysis databases such as those offered by players like SQreamTechnologies, technological solutions abound to help best draw rapid insights from large volumes of data.
But how exactly can governments turn this data analysis into concrete federal programming, designed to protect the lives of citizens? Here are a few areas which can benefit enormously from accurate analysis of big data.
The management of transportation suffers from any number of variable factors, including weather conditions and driver ability, but big data analysis can ensure that both federal and local governments are able to plan ahead. For instance, based on analysis of traffic movements, greater numbers of traffic officers can be allocated to specific locations, and better traffic calming measures can be installed at accident hotspots.
SPATIOWL by Fujitsu is one of the most developed services that deal with data coming from public transportations, vehicles, and pedestrians’ smartphones in urban areas through sensors.
